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3 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Künstlerbuch | John Gerrard – Neural Exchange

Design, Layout, Printmanagement

John Gerrard : Neural Exchange

Künstlerbuch

315 x 235 mm, english

36 pages , Artist Zine

LACMA Los Angeles Count Museum of Art, 2017

JOHN GERRARDNEURAL EXCHANGE

4 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Künstlerbuch | John Gerrard – Neural Exchange

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IntroductionJoel Ferree and Amy Heibel

Since 2014, the Art + Technology Lab at the Los Angeles County Museum of Art (LACMA) has supported artist experiments that engage emerging technology. Through its technology sponsors, the Lab provides grants, in-kind support, and facilities at the museum to artists to develop new projects.

An Art + Technology Lab grant is not a commission. It is not an exhibition. It is a form of support that allows artists to pursue new directions in their practices, to take purposeful risks, and to develop projects that wouldn’t be done otherwise. In a highly quantified world that places a premium on deliverables, it sets out to create a space that emphasizes process over product and teases out the conversations that result from such experimentation.

John Gerrard came into the Lab program with a proposal to use gaming technology to render a large-scale image in real time. After meeting with advisors John Suh of Hyundai, Brian Mulford of Google, and Bryan Catanzaro of NVIDIA, Gerrard became interested in neural networks. Shortly thereafter, he submitted a new project proposal, this one for what would eventually become Neural Exchange (Leaf Covered Figure) 2017.

Artificial neural networks mimic the network of neurons in the brain, but on a smaller scale. In short, they allow computers to learn from data. First, a training set of data is introduced, then the computer uses the training set to identify or generate new data based on what it has already “learned.” For example, a training set of 100 cat images can be introduced and “learned” by a machine to help it identify new cat images. Gerrard originally sought to put this kind of machine learning into practice in his work, “hand-building” a digital model similar to a character found in a battle-simulation game and employing the character’s vernacular martial gestures as a training set to produce new gestures. The artist considered this to be a machine-generated militaristic choreography.

Following discussions with Lab advisors—specifically at Google— the decision was made to move beyond “found” animations and to generate unique captures using a special suit embedded with sensors. This converts action into data at multiple points in space and time. In addition, the focus moved from military-simulation games to martial arts performances—specifically kata in karate, in which a precise series of gestures is performed by a group simultaneously. Later still over the year-long research period, the results of these captures were deemed too aggressive, and the studio began to work with a ballet dancer, Esther Balfe.

Working with Balfe and accounting for the computing needs and processing time necessary to train a neural network, a group of four core movements was developed. It includes two that travel backward and two forward—each easily identifiable. This training set was performed by Balfe hundreds of times, as repetitions, captured as data and used to train the network over multiple iterations. Once learned, the neural network uses these actions to develop a choreography—a sort of perpetual choreographic generator existing outside of traditional animation techniques. It is this idea of a choreographic generator that has become the core area of research for Gerrard’s studio with respect to the Art + Technology Lab grant.

Toward the end of the research period, developing a basic kind of interaction between two dancing figures became important. As a neural network cannot be programmed—but must learn—a new training set had to be developed, which two characters are captured responding to each other‘s actions. Usually this meant a backward movement was matched or responded to with a forward one. The research has resulted in these two outcomes: one performance of a perpetual dance generated by the neural network and another in which two characters also dance with no duration, but in which a basic interaction can be witnessed.

The performers in the final work are figures dressed in leaf-covered “Gillie” suits, a type of camouflage clothing that the artist also saw as referring to the old European tradition of the “green” or “wild” man. Gerrard’s team went out into the woods of Vienna to shoot a model dressed in this clothing. The images were the basis for a virtual 3-D model—the “leaf-covered figure” used in the final performance.

Within the parameters of the neural network there is an un-predictability in the final movements that are generated. Natural human variation in the core training set of four motions means that their interpretation and representation are producing some novel results and unexpected outcomes. The artist has stated:

I have this strange feeling that I am equipping my engine—via

the [neural network]—with a kind of an imagination. I frame

that imagination through the kind of actions that are captured;

however, looking at the leaf-covered figure perform, as I am

doing now, something else is emerging...

Joel Ferree, Program Director, Art + Technology Lab

Amy Heibel, Adjunct Curator, Art + Technology Lab

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Neural Exchange Brian Mulford

1) In both theory and practice, what is a neural network?

Neural networks (NNs) are everywhere. You can see them in how your Facebook and LinkedIn connections cluster in groups around family, work, friends, and acquaintances. You can see them in the relationship between states and cities on a map, and in the way flowers grow across fields. NNs are anywhere where objects or entities cluster and disburse with explicit relationships to one another. The fact that we see these interconnected relationships occurring in common contexts, it helps stage how mathematical NNs are formed as a series of simple ties between things. Applied in computer science, NNs extend the concept to indicate a method of analyzing nonlinear numerical tensors (data that forms arrays of arrays) so as to apply concrete classifications to objects—typically in order to measure and proscribe unitary value, which is then used for prediction. When performed electronically on a large scale, we generally call it deep-learning machine learning (DLML). The “deep-learning” portion relates to the many layers of relationships being summed up and passed to subsequent layers. Let’s explore what linear and nonlinear mean in this context. Linear data or lists of numerical factual representations compared to other sets of linear data will produce easily recognized models. For instance, a set of data representing age and another representing height can be plotted along two axes and show a steady left-to-right pattern where height increases with age and then tapers off. This is called linear data, in that it produces a relatively smooth line with values appearing discretely above and below the line division. Nonlinear data is more complicated. Imagine, instead of a smooth line separating values into two distinct areas, the data points when separated form an S curve with values appearing all over the chart. This is much harder to understand and predict. For example, if we add dietary factors, genetic factors, health, geography, current elevation, and favorite genre of film to our hypothetical model of age/height, it would be nearly impossible to plot in a chart. This is an example of nonlinear data: abstract problems that have so many widely changing variables that standard methods of analysis aren’t able to make meaningful inferences from the data. NNs provide a set of methods (some optimized for data relating to time or sequences, or self-organizing data) for making sense of highly varied data. These methods result in being able to classify (e.g., this picture is a cat) or predict values (e.g., you will probably like this movie) in such a way that isn’t readily visible when looking at data using traditional methods (e.g., databases or charts). Machine learning (ML) enables this to occur at a high scale and to store the classification and logical values so that they may be compared with new data or take on new data, creating a cycle where existing data helps organize future data.

Examples of where you see ML being applied range from how Gmail automatically detects spam and junk email, to what movie recommendations you see, to predicting crop yields or weather. Practically speaking, NNs work by observing structures present within information encoded into representational numerical data sets. In fact, in today’s environment, 70 to 80 per cent of ML is tied up in creating numerical representations of data (features) and applying meaningful descriptions (labels) to them. The rest is applying various NN methods for analyzing and testing the data (models). The core of NNs is in what’s called hidden layers. These layers are abstractions of numerical ranges between data sets that over many iterations form groups or clusters of distances between numbers. These abstractions represent logical groups of information and pass it to deeper layers for further clarification. This process is called training—the core of which becomes the recognition model and subsequent output used for rapid identification, object classification, and prediction. When we think about the graph made by our connections on Facebook (people that we connect to, organized by strongest to weakest), it’ll resemble a series of clusters, with densely connected lines and elongated, dispersed lines between clusters. To an NN, the inputs would be all the people in your friends list and all the communications between them and the output would be the graph showing your most important relationships. The model would be the established patterns it forms that would allow any new friends joining your network to be quickly classified into the graph. It even could predict other people not in your friend list who would be strong connections. With that description in mind, consider how much of the world can be categorized as series of weighted connections. Think about how we as humans interpret conditions based upon prior experience, known interactions, and physical properties, and make predictions as to what it all means. ML makes it interpretable via a computer, which is often many times more accurate than what people can calculate independently. For instance, ML models for image recognition can “memorize” billions of pixel gradients and recall them with perfect accuracy, whereas the human mind will start to lose recall after fewer than a hundred. Trying to recognize a thousand hieroglyphic symbols would be taxing and time consuming for most people, but for ML it would be easy and quick to generalize the shapes and recognize them with accuracy in moments.

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3) Conversely, what risks might this technology hold—socially, economically, or otherwise?

Thoughts of superintelligent, malevolent AI may capture the imagination, but I’m worried about two more concrete risks that are closer at hand. First, AI may increase inequality in our society. Because AI is easy to replicate, a few people applying AI can make big changes in how we do many things. This will change the nature of work for many people, and may displace jobs, especially in the short term. For example, truck driver is one of the most common occupations in the United States in 2017, but autonomous long-haul trucks may replace many truck drivers. What will they do for their next job? How will we educate them to do something else? I’m concerned about how people will adjust, even though if I think long-term, this transition will be good for all of us. As a society, we’re going to need to figure out how people will find meaning and purpose without the jobs that give people structure today. I believe this is possible, although challenging. It will require new policies, with a lot more redistribution, so that the people benefiting financially from AI are helping those being displaced. I hope it also gives people much more time for art, community building, and the humanities: those things that we know enrich our lives, but that are currently not compensated well monetarily. I spent two years volunteering full-time, trying to make the world a better place, working with individuals personally, and those two years were some of the most purposeful, intentional, and focused years of my life, despite the fact that I wasn’t paid. I hope that AI frees up our time so that as a society we can give more people the opportunity to do similar things. I hope AI gives us the freedom to lift our sights and translate more of our idealism into reality, because it will liberate the human capital currently being spent on tedious labor.

Second, AI will create more compelling tools with which to manipulate society. Propaganda will be far more compelling, honed by AI to garner more attention. “Fake news” will include convincing-looking videos of people saying things they didn’t say. We will have news scandals driven by fake videos of political candidates saying things they never said that will look extremely convincing. We’ll need new ways to authenticate images, video, and audio, because it will become too easy to conjure up fake materials. People will attempt to use AI to manipulate democracy, and differentiating between truth and fiction will likely be even harder. I’m more concerned with the impact of AI on our societal institutions and economy than the possibility of malevolent AI, like the Terminator or even HAL 9000. Truly sentient, superintelligent agents are still far away in a technological sense. Just as there were connections between the Industrial Revolution and the Communist Revolution, the rise of AI will lead to political strains on our systems that will challenge the way we think about the world and our place in it. I’m more worried about the political instability that may arise during this transition than the technology itself.

Bryan Catanzaro is Vice President of Applied Deep Learning Research

at NVIDIA, where his mission is to find new ways of improving NVIDIA’s

work by applying AI. He received his PhD in Electrical Engineering and

Computer Sciences from the University of California, Berkeley, after

earning a BA in Russian.

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Künstlerbuch | Ramesch Daha – Unlimited History5 / 55 | ce–design_CarolineEcker_SelectedWorks_1801

Materialauswahl, Design, Layout, Editing, Koordination,

Printmanagement

Ramesch Daha : Unlimited History

Künstlerbuch

235 x 297 mm, english–german

192 pages , Artist Book

Revolver Publishing, Berlin, 2016

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Faksimile


106 pages , 1:1 Reproduction of an Artist Diary

including original frottage

Vienna, 2015

Ramesch Daha : Research Diary

Künstlerbuch; Faksimile | R. Daha – Research Diary

Materialauswahl, Design, Layout, Reprographik,

Printmanagement

8 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Künstlerbuch; Faksimile | R. Daha – Research Diary


Sabine Ott : Fragile

Künstlerbuch


192 pages, Artist Edition

Triton, Barcelona / Vienna, 2015

Künstlerbuch | Sabine Ott – Fragile

Design, Layout, Printmanagement

https://www.youtube.com/watch?v=W-s8ACjE-TY

10 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Künstlerbuch | Sabine Ott – Fragile


The 2nd City: Dynamic Raumplan

Ausstellungskatalog; Coop Himmelb(l)au – The 2nd City: Dynamic Raumplan;

anläßlich der gleichnamigen Ausstellung; SCI–Arc Gallery,Southern Californian

Institute of Architecture, L.A., USA, 2015

292 x 216 mm, 40 Seiten, english Edition

Design, Layout, Infografik, Projektmanagement

Ausstellungskatalog | The 2nd City

12 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungskatalog | The 2nd City

13 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Gebäudemonographie | Dalian Internat. Conference Center

COOP HIMMELBLAU:Dalian International Conference Center

Gebäudemonographie für Coop Himmelb(l)au; anläßlich der Realisierung des

gleichnamigen Gebäudes in Dalian, China, Preface by Joseph Giovannini


ORO Publishing Group, 2014/2015

Materialauswahl, Design, Layout, Text, Editing, Koordination,

Kommunikation, Projektmanagement

14 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Gebäudemonographie | Dalian Internat. Conference Center


Say himmelb(l)au.

Ausstellungskatalog anläßlich der Ausstellung:

„COOP HIMMELB(L)AU : 7+

Projects, Models, Plans, Sketches, Statements.“

Gallery Aedes (Ed.): Say Himmelb(l)au. Berlin, 2012

Based on the lecture: Wolf D. Prix: „What‘s the difference“,

SCI–Arc Southern California Institute of Architecture,

Los Angeles, USA, 09/11/2011

Essays by Kristin Feireiss & Hans Jürgen Commerell,

Michael Mönninger and Wolf D. Prix


Ausstellungskatalog | Say Himmelb(l)au

Design, Layout, Final Artwork

16 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungskatalog | Say Himmelb(l)au

17 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Kalendarium 2015 | Coop Himmelb(l)au

Kalendarium 2014 / 2015

Jahreskalender für Mitarbeiter, Freunde & PartnerEdition mit perforiertem und leporellogefalztem Bastelbogen 176 x 182 mm, 234 SeitenHardcover mit Silberfolienprägedruck, fadengebunden, offener Rücken & Schmuckbanderole; nummeriert und limitiert

Design, Layout, Text Editing, Projektmanagement

18 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Kalendarium 2015 | Coop Himmelb(l)au

AUSSTELLUNGSGESTALTUNG


Geister · Gold · Schamanen

Ausstellungsdesign / Grafik / Illustration

in Kooperation mit Atelier Ramesh Biswas

Fahnen, Infopanele, Vitrinengestaltung,

Objektbeschriftungen

anläßlich der Ausstellungs „Geister Gold Schamanen“

Schlossmuseum Linz, 2007

Ausstellungsgestaltung | Geister Gold Schamanen

21 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Geister Gold Schamanen

22 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Geister Gold Schamanen

23 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Kopfüber in die Nacht

Kopfüber in die Nacht.Fledermäuse in Schloß und Au

anläßlich der Ausstellungs„Kopfüber in die Nacht“

Schloß Orth – Nationalpark Donauauen, 2017

in Kooperation mit M. Blum

Design, Installationen, Layout, Illustrationen

24 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Kopfüber in die Nacht


Das Himmelb(l)au Projekt.Frankfurt | Lyon | Dalian

Ausstellungsdesign & Grafik für Coop Himmelb(l)au;

anläßlich der Ausstellung:

Das Himmelb(l)au Projekt. Frankfurt, Lyon, Dalian

Einzelausstellung CHB(L) / 05/2015–08/2015 /

DAM Deutsches Architekturmuseum, Frankfurt/M.

Inhalt: 3 Großprojekte

Wandfries: 130 x 2,5 m

Projekttafeln: 3 Projekte auf 46 Panels je 1 x 2 m

Ausstellungsgestaltung | Das Himmelb(l)au Projekt

26 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Das Himmelb(l)au Projekt

Wandfries: 130 x 2,5 m

46 Projektpanels Größe: 1 x 2 m

27 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Das Himmelb(l)au Projekt

28 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Mind Expanders

“Mind Expanders. Performative Körper –Utopische Architekturen um ´68“

Ausstellungsdesign für Coop Himmelb(l)au;

Materialzusammenstellung & –aufbereitung,

Projektmanagement, Koordination, Kommunikation

anläßlich der Ausstellungsbeteiligung CHB(L)s

MUMOK Wien / 2008

29 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Ausstellungsgestaltung | Mind Expanders

KOMMUNIKATIONS– & INFORMATIONSGRAFIK /ILLUSTRATION

31 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Bildbearbeitung | Plandarstellung

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Central L

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UFA Cinema Center, D

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COOP HIMMELB(L)AU Wolf D. Prix & Partner ZT GmbH, Vienna, Austria

COOP HIMMELB(L)AU Europe GmbH

COOP HIMMELB(L)AU France S.A. de R.L.

CLOUD INC. L.A. Los Angeles, USA

COOP HIMMELB(L)AU Baku

COOP HIMMELB(L)AU Hong Kong LTD.

ASIAEUROPEAMERICA

COOP HIMMELB(L)AU Beijing

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36 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Infografik | Statistik

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0802 Opera Pavilion Munichm 1:100

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0804 DCC Dalian International Conference Centerm 1:100

0701 House of M

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0306 ECB Frankfurtm 1:1000

0018 Musee Confluences Lyonm 1:100

0711 Museum of Contemporary Art & Planning Exhibitionm 1:100

NF26.700 m²

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Volume195.206 m³

Building Costs: € 150 Mio

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SEG APARTMENT BLOCK REMISE Vienna, Austria, 1994–2000

APARTMENT TOWERS "WIENERBERG CITY" Vienna, Austria, 1999–2004

APARTMENT BUILDING GASOMETER B Vienna, Austria, 1995–01

APARTMENT AND OFFICE BUILDING SCHLACHTHAUSGASSE Vienna, Austria, 2001/03–05

APARTMENT BUILDING "LIESING BREWERY" Vienna, Austria, 2002/06–11

BMW WELT Munich, Germany, 2001–07

Akron Art Museum Akron, USA, 2001–07

BUSAN CINEMA CENTER Busan, Korea, 2005–12

PAVILION 21 MINI OPERA SPACE Munich, Germany, 2008–10

MARTIN LUTHER CHURCH Hainburg, Austria, 2008–11

DALIAN INTERNATIONAL CONFERENCE CENTER Dalian, China, 2008–12

MUSÉE DES CONFLUENCES Lyon, France, 2001/2010–14

MUSEUM OF CONTEMPORARY ART & PLANNING EXHIBITION Shenzhen, China, 2007-2015

EUROPEAN CENTRAL BANK (ECB) Frankfurt/M., Germany, 2003–14

HOUSE OF MUSIC II Aalborg, Denmark, 2003/2008–13

HIGH SCHOOL #9 FOR THE VISUAL AND PERFORMING ARTS Los Angeles, USA, 2002–08

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0 1000 2000

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30 846 m²






0102 BM

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1:100

0105 Akronm 1:1000




0701 House of M

usic IIm

1:100




NF26.700 m²

BGF46.476 m²

Volume195.206 m³





‘10 ‘11 ‘122008 ‘09 ‘10 ‘11 ‘12

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‘11 ‘12 ‘13‘10‘09‘08‘07‘06‘05‘04‘03‘022001

















3 868 €/m²0 1000 2000 1000


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2014

Star

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‘11 ‘12 ‘13‘10‘09‘08‘07‘06‘05‘042003

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petit

ion

‘13‘12‘11‘10‘092008

Com

plet

ition

Star

t of C

onst

ruct

ion

Open

ing

since 2000

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME

56 814 m³

13 702 m²

11 650 m²

80 000 m³

27 900 m²

23 700 m²

69 240 m³

71 000 m³

21 605 m²

18 360 m²

36 000 m²

30 600 m²

531 000 m³

73 000 m²

62 050 m²

6 045 m²

5 140 m²

252 473 m³

31 138 m²

21 204 m²

VOLUME BGF NF

349 708 m³

57 981 m²

51 067 m²

VOLUME BGF NF

4 350 m³

560 m²

430 m²

289 m²

245 m²

1.450.000 m³

1.080.000 m³

VOLUME BGF NF

VOLUME BGF NF

117 650 m²

100 100 m²

185 000 m²

157 250 m²

195 206 m³

46 476 m²

26 700 m²

132 000 m³

35 000 m²

31 500 m²

BGF NF

2 521 €/m²

4 594 €/m²

0 1000 2000

0 1000 2000 3000 4000

3 227 €/m²0 1000 2000 3000



€

€

3 750 €/m²0 1000 2000 3000


2 514 €/m²0 1000 2000


€

1 724 €/m²0 1000


0 1000 2000 3000



0 1000 2000


€895 €/m²

0 1000


1 100 €/m²0 1000


1 075 €/m²0 1000


1 350 €/m²0 1000


1 076 €/m²0 1000


Com

plet

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2014

Star

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ion

‘11 ‘12 ‘13‘10‘09‘08‘07‘06‘05‘042003

Star

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ion

AUWERKEB

2 619 €/m²0 1000 2000


2 496,20 €/m²€/m²

BGF

0 1000 2000

€

30 846 m²






0102 BM

Wm

1:100

0105 Akronm 1:1000




0701 House of M

usic IIm

1:100




NF26.700 m²

BGF46.476 m²

Volume195.206 m³





‘10 ‘11 ‘122008 ‘09 ‘10 ‘11 ‘12

Star

t of P

lann

ing

Star

t of C

onst

ruct

ion

Open

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Com

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3 868 €/m²0 1000 2000 1000


Star

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2014

Star

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‘11 ‘12 ‘13‘10‘09‘08‘07‘06‘05‘042003

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ion

‘13‘12‘11‘10‘092008

Com

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Star

t of C

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since 2000

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME

56 814 m³

13 702 m²

11 650 m²

80 000 m³

27 900 m²

23 700 m²

69 240 m³

71 000 m³

21 605 m²

18 360 m²

36 000 m²

30 600 m²

531 000 m³

73 000 m²

62 050 m²

6 045 m²

5 140 m²

252 473 m³

31 138 m²

21 204 m²

VOLUME BGF NF

349 708 m³

57 981 m²

51 067 m²

VOLUME BGF NF

4 350 m³

560 m²

430 m²

289 m²

245 m²

1.450.000 m³

1.080.000 m³

VOLUME BGF NF

VOLUME BGF NF

117 650 m²

100 100 m²

185 000 m²

157 250 m²

195 206 m³

46 476 m²

26 700 m²

132 000 m³

35 000 m²

31 500 m²

BGF NF

2 521 €/m²

4 594 €/m²

0 1000 2000

0 1000 2000 3000 4000

3 227 €/m²0 1000 2000 3000



€

€

3 750 €/m²0 1000 2000 3000


2 514 €/m²0 1000 2000


€

1 724 €/m²0 1000


0 1000 2000 3000



0 1000 2000


€895 €/m²

0 1000


1 100 €/m²0 1000


1 075 €/m²0 1000


1 350 €/m²0 1000


1 076 €/m²0 1000


Com

plet

ion

2014

Star

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lann

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ion

‘11 ‘12 ‘13‘10‘09‘08‘07‘06‘05‘042003

Star

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AUWERKEB

2 619 €/m²0 1000 2000


2 496,20 €/m²€/m²

BGF

0 1000 2000

€

30 846 m²






0102 BM

Wm

1:100

0105 Akronm 1:1000




0701 House of M

usic IIm

1:100




NF26.700 m²

BGF46.476 m²

Volume195.206 m³





‘10 ‘11 ‘122008 ‘09 ‘10 ‘11 ‘12

Star

t of P

lann

ing

Star

t of C

onst

ruct

ion

Open

ing

Com

plet

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2008 ‘09 ‘10 2011

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‘13‘12‘11‘10‘092008

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Star

t of C

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since 2000

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME BGF NF

VOLUME

56 814 m³

13 702 m²

11 650 m²

80 000 m³

27 900 m²

23 700 m²

69 240 m³

71 000 m³

21 605 m²

18 360 m²

36 000 m²

30 600 m²

531 000 m³

73 000 m²

62 050 m²

6 045 m²

5 140 m²

252 473 m³

31 138 m²

21 204 m²

VOLUME BGF NF

349 708 m³

57 981 m²

51 067 m²

VOLUME BGF NF

4 350 m³

560 m²

430 m²

289 m²

245 m²

1.450.000 m³

1.080.000 m³

VOLUME BGF NF

VOLUME BGF NF

117 650 m²

100 100 m²

185 000 m²

157 250 m²

195 206 m³

46 476 m²

26 700 m²

132 000 m³

35 000 m²

31 500 m²

BGF NF

2 521 €/m²

4 594 €/m²

0 1000 2000

0 1000 2000 3000 4000

3 227 €/m²0 1000 2000 3000



€

€

3 750 €/m²0 1000 2000 3000


2 514 €/m²0 1000 2000


€

1 724 €/m²0 1000


0 1000 2000 3000



0 1000 2000


€895 €/m²

0 1000


1 100 €/m²0 1000


1 075 €/m²0 1000


1 350 €/m²0 1000


1 076 €/m²0 1000


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2014

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‘11 ‘12 ‘13‘10‘09‘08‘07‘06‘05‘042003

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2 619 €/m²0 1000 2000


2 496,20 €/m²€/m²

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0 1000 2000

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30 846 m²

37 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Illustration | Infografik | Anatomische Darstellung

Microchiroptera

OBERARMKNOCHEN

UNTERARMKNOCHEN (ELLE & SPEICHE)

HANDWURZELKNOCHEN

MITTELHANDKNOCHEN

FINGERKNOCHEN

OBERARMKNOCHEN


HANDWURZELKNOCHEN

MITTELHANDKNOCHEN

FINGERKNOCHEN

OBERARMKNOCHEN


HANDWURZELKNOCHEN

MITTELHANDKNOCHEN

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FRÜHLINGSBEGINN19./20./21.März 22./23./24.September

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GEBURT | AUFZUCHT | PAARUNG

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Illustration / Installation | Infografik : Lebensrythmus


0

20

0

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60

80

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FREQUENZ (kHz)

MÜCKENFLEDERMAUS

0

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ABENDSEGLER

Hörbilder / Echoortung

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Illustration | Infografik | Wissenschaftliche Darstellung

VISUAL IDENTITY | CI/CDWERBEGRAFIK

41 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Werbemittel | Flyer / Plakat


Gärtnerhof OchsenherzFuchsenwaldstraße 902230 Gänserndorf-Süd

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ZVR: 302173226

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[email protected]

JA,

ES GIBT

NOCH FREIE

KISTLPLÄT

ZE

!

NUR GEMÜSE?

Wo bekomme ich mehr Infos?

Wie funktionierts?

Warum?

gemeinsam landwirtschaftengemeinsam landwirtschaften

Wie funktionierts?

Wo bekomme ich mehr Infos?

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VIELFALT

FRISCHE

QUALITÄT

MMMHHH...

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in Wien, Gänserndorf oder Mödling• wöchentlich neue und auf das Kistl abgestimmte Rezepte


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VIVA ROSSINI!

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Vorverkauf: 15 € / 8 €* | Abendkasse: 18 € / 10 €* | Karten unter www.oeticket.com

©JE

SÚS

GA

BÁN

SZENEN, DUETTE & ARIEN ZUM 225. GEBURTSTAG

OPERNGALA ANLÄSSLICH

DER BEZIRKSFESTWOCHEN

SZENEN, DUETTE & ARIEN ZUM 225. GEBURTSTAG VIVA ROSSINI!

©JE

SÚS

GA

BÁN

29–05–2017

19:30

*Ermäßigung für Studenten, Abeitssuchende, Pensionisten

MONTAG, 29. MAI 2017 | 19.30 UHRFESTWOCHENKONZERT BEZIRKSAMT LANDSTRASSE

BORROMÄUSSAAL KARL–BORROMÄUS–PLATZ 3, 1030 WIEN

Vorverkauf: 15 € / 8 €* | Abendkasse: 18 € / 10 €* | Karten unter www.oeticket.com

OPERNGALA ANLÄSSLICH

DER BEZIRKSFESTWOCHEN

SZENEN, DUETTE & ARIEN ZUM 225. GEBURTSTAG VIVA ROSSINI!

45 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 CI / CD | UIAG Unternehmensinvest AG

// ce–design // Caroline Ecker // 09/2015 // 2 / 9

Analyse Logo

uiagUIAG

Font

Wortbild

Bildmarke

Unternehmens Invest AG


Wort/Bildmarke uiag

Balkendiagramm, einfach, klar, stark, seriös, aufsteigend,gut eingeführt, bewährtsollte als Ikone erhalten bleiben, kann adaptiert & integriert werden

Wiedererkennungswert ist nicht gegeben, suggeriert eine Neudefinition des Unternehmensnicht empfehlenswert.

Bildmarke

Wortbildmarkeuiag


CE–DesignCaroline EckerPressgasse 22/161040 WienAustria

Betreff: Geschäftsbrief 24/09/2015

Sehr geehrte Damen und Herren,

Et adit laut aut estium fugiatumet ad quam volorrovit es et occus, con et odis deresci-mus, cuptatur andebis eos que aut recum et harumque landiat.Ignam et restrum quatur sit, testrum ilitaes aut fugiasperes quo eos ius doluptiae quia dolora sum iuntur? Ant.Erspitatem ra nonsectia volupta tetur?Ut et et omnima etur aut ut ped que landisquiam ut a pos voluptatusam rem voluptium res si ommo offictem hit labore, vel imo estisqui velendandit ut intotam reperibeat.Unt aspitati consed quas molupti busae. Dunt acim audam dolum excesti delia non re, utaqui conest, tem simincilleni dolupta ererovit, quis dolor moluptatur?Ihillor porrovide nusa sum, aut pa deratus, alicae apeliam fugit faces earcimod quam qui volor sus eiur re volores undipiendit perum ra autemporis dunt id moluptate parumquis pro cum cus.Umquia qui rehenda que moluptate moluptatius aspita quo tem esti quam et fugite del eius exerrunt vendit utatur aut a nonsecatis modia ipsam si re consenduciet dolupti oreste eosaes sunt laborrum rehenis volluptios sit, sitatio nsediat dolupti aeperia dunt imagnisquis sim res ma simporibus es este et faccate dolut ratempor antempe rundan-dam, ullorep tature remodis voluptas magnimi nctumqui dunt eos ulluptur soloreiume pelecus cor ad experum aceate mo et volor as aut volor resti inciam et esto inulloreniat quisci aut latin consequis exceaquo cor modis eiumquatur?Itiuribus alitaeribus, ut as il inient doloren dipiciis aut porum lam natem quam volor at qui cus, acepres dolesendam eium fugia qui repta nissequ oditam et qui omnissi numquis sunt.

Beste Grüße,

Xyz Vonxyz





Beste Grüße,

Xyz Vonxyz





Beste Grüße,

Xyz Vonxyz

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Vergleich : Geschäftsbrief

// ce–design // Caroline Ecker // 10/2015 //

LOGO UIAG

ROT: RAL 3020CMYK: 0 100 100 10RGB: 210 10 17

UIAG.pdfUIAG.epsUIAG.jpg

UIAG_font.pdfUIAG_font.epsUIAG_font.jpg

UIAG_UnternehmensInvestAG.pdfUIAG_UnternehmensInvestAG.epsUIAG_UnternehmensInvestAG.jpg


UNTERNEHMENS INVEST AGUNTERNEHMENS INVEST AG

UNTERNEHMENS INVEST AGUNTERNEHMENS INVEST AG

LOGO Variante #1


UNTERNEHMENS INVEST AG UNTERNEHMENS INVEST AG

UNTERNEHMENS INVEST AG

LOGO Variante #2





LOGO Variante #3



Logo – TR Technical Regulations

HPE-grün:RGB 0/179/136CMYK 80/0/60/0HEX #00B388PMS 339

LogoTR > CMYK .jpg .png .pdf .eps

LogoTR_rgb > in RGB .svg

TR > in CMYK .jpg .png .pdf .epsTR_rgb > in RGB .svg

LogoTR

TR


#4

#5

male-female

male-female

Logoimplementierung : T-shirts


Logoimplementierung : Geschäftsbrief

Muster MenschFirmaMusterstrasse 11234 StadtLandEuropeWeltUniversum

Dear Ladies and Gentlemen,

Sedigend ignamus torepe prae core nonet eatum reptaecullor sime nectem rero molectemquat faciat.

Deniend aepedi ipsam, sam iust ligendest etur, qui am sunt es inctisq uodicat-quo mos audi voluptatiur? Quidi dolupita volut labore idit endi omnias ditatur, omnis autate lanimax imusaes molupta tectas simus, to ium corum auda sitatur si doloritiscim simagnat fuga. Nemporum untiamus, qui dollenihit ut explicie-tur sam ea se eosandi aspid ut eliantia et rati aut qui occae voloreptio. Ut pro eaquam, nobit et quo et et modis estio est, cuptatum que nis expel il mo berchil intibus dantion con plam esti adi berempelibus aspe pe dus, consequ asintibus sequam faccusd andunte dictisi alignita dolum, comnihiliqui beri conecab orerior as molupta ectatem eost, ius autempori repudae voloria dem ereprat enduscia soloriate veliquis quationsecum volut lamet fuga. Cerunt, cora dictaturi digenima nonsedi nobitatintor alicill iberit ex et pedicidel ipsam invero mo mi, officte mpelige ndebissit aut facepudi que peleni blabo. Explaut quodigentiam ipsum simusda nihicit ulla nusciis ese consed eruptatur aruptio es aut aut facero occuptation estiur? Imusaeribus nonseque vendae dolorrum quo molupta dem fugia corum rehentio. Gita dolor atur aborro con plit quiate eos aut as re veligenia quata veliat.

My best regards,

Mensch Muster

JJJJ/MM/TTxyBetreff: Geschäftsbrief

Technologiestrasse 5Block F1120 Wien AustriaTel.: +43 1 XXX XX XX-0 Fax: +43 1 XXX XX XX-0 E-Mail: [email protected]

Rechnungsmerkmale, Bankverbindung, UID, HPE-Verweis, Handelsregister, Bankverbindung, UID, HPE-Verweis, etc, Steuer,




Deniend aepedi ipsam, sam iust ligendest etur, qui am sunt es inctisq uodicat-quo mos audi voluptatiur? Quidi dolupita volut labore idit endi omnias ditatur, omnis autate lanimax imusaes molupta tectas simus, to ium corum auda sitatur si doloritiscim simagnat fuga. Nemporum untiamus, qui dollenihit ut explicie-tur sam ea se eosandi aspid ut eliantia et rati aut qui occae voloreptio. Ut pro eaquam, nobit et quo et et modis estio est, cuptatum que nis expel il mo berchil intibus dantion con plam esti adi berempelibus aspe pe dus, consequ asintibus sequam faccusd andunte dictisi alignita dolum, comnihiliqui beri conecab orerior as molupta ectatem eost, ius autempori repudae voloria dem ereprat enduscia soloriate veliquis quationsecum volut lamet fuga. Cerunt, cora dictaturi digenima nonsedi nobitatintor alicill iberit ex et pedicidel ipsam invero mo mi, officte mpelige ndebissit aut facepudi que peleni blabo. Explaut quodigentiam ipsum simusda nihicit ulla nusciis ese consed eruptatur aruptio es aut aut facero occuptation estiur? Imusaeribus nonseque vendae dolorrum quo molupta dem fugia corum rehentio. Gita dolor atur aborro con plit quiate eos aut as re veligenia quata veliat.

My best regards,

Mensch Muster



Tel.: +43 1 XXX XX XX-0 Fax: +43 1 XXX XX XX-0 E-Mail: [email protected]

Technologiestrasse 5Block F1120 Vienna | Austria




Deniend aepedi ipsam, sam iust ligendest etur, qui am sunt es inctisq uodicat-quo mos audi voluptatiur? Quidi dolupita volut labore idit endi omnias ditatur, omnis autate lanimax imusaes molupta tectas simus, to ium corum auda sitatur si doloritiscim simagnat fuga. Nemporum untiamus, qui dollenihit ut explicie-tur sam ea se eosandi aspid ut eliantia et rati aut qui occae voloreptio. Ut pro eaquam, nobit et quo et et modis estio est, cuptatum que nis expel il mo berchil intibus dantion con plam esti adi berempelibus aspe pe dus, conse-qu asintibus sequam faccusd andunte dictisi alignita dolum, comnihiliqui beri conecab orerior as molupta ectatem eost, ius autempori repudae voloria dem ereprat enduscia soloriate veliquis quationsecum volut lamet fuga. Cerunt, cora dictaturi digenima nonsedi nobitatintor alicill iberit ex et pedicidel ipsam invero mo mi, officte mpelige ndebissit aut facepudi que peleni blabo. Explaut quodigentiam ipsum simusda nihicit ulla nusciis ese consed eruptatur aruptio es aut aut facero occuptation estiur? Imusaeribus nonseque vendae dolorrum quo molupta dem fugia corum rehentio. Gita dolor atur aborro con plit quiate eos aut as re veligenia quata veliat.

My best regards,

Mensch Muster


Technologiestrasse 5Block F1120 Wien AustriaTel.: +43 1 XXX XX XX-0 Fax: +43 1 XXX XX XX-0 E-Mail: [email protected]


#1.1 #1.2 #1.3


Logoimplementierung : .ppt Präsentation

TECHNICAL REGULATIONS : CALCULATIONS

TECHNICAL REGULATIONS : CALCULATIONS

Title // xy // JJJJ/MM/DD

Title // xy // JJJJ/MM/DD

4:3

16:9

CI / CD | TR Technical Regulations


Red Rooster IT Gmbh | Hackhofergasse 1 | A – 1190 Wien [email protected] www.redrooster-it.com

FN: 321522b | UID: ATU 64613378 | Hypo Landesbank | bLZ: 58000 | Kto: 20456693017 | IbAN: AT555800020456693017 | SWIFT: HYPVAT2b

Red Rooster IT Gmbh | Hackhofergasse 1 | A – 1190 Wien

Christian ECkEr

Managing Director

+ 43 664 884 540 56

christian.ecker@

redrooster-it

.com

www.redrooste

r-it.com

Red Rooster IT

Gmbh | Hackhofergasse

1 | A – 1190 Wien

PEtEr kiEnEr

Managing Director

+ 43 664 884 540 55

[email protected]

www.redrooster-it.com

Red Rooster IT Gmbh | Hackhofergasse 1 | A – 1190 Wien

riChard Fallon Director

+ 43 699 190 837 75 [email protected]

www.redrooster-it.com

Red Rooster IT Gmbh | Hackhofergasse 1 | A – 1190 WienBi Consulting & development

CI / CD | Red Rooster IT


&eronika reiter

artin Seidl

u.a

.w.g

. | 0

650

821

16 7

0 |

0699

102

730

79

samstag, 19. september 2009

14:30 uhr treffpunkt

kirche st. nikolaus in golling | torren

anschliessend laden wir zur

hochzeitsfeier

hofbräu kaltenhausen | ruperti g’wölb

..und freuen uns, wenn du mit uns feierst!

wir heiraten..

..und freuen uns, wenn du mit uns feierst!

wir heiraten..

Freitag, 18. September 2009

10:30 Uhr treFFpUnkt

StandeSamt SchloSS mirabell | SalzbUrg

CI / CD | Wedding

PRODUCT DESIGN


TIME 4 PLAY – Plattenspiele

Time4Play–Plattenspiele ist eine Neuinterpretation bekannter

Brettspielklassiker für Spielende ab 3 Jahren.

Die siebgedruckten Spielplatten werden gleich einer Langspielplatte

in ihrer Hülle aufbewahrt, die beton-gegossenen Steine in einer

maßgeschneiderten Schachtel.

Limitierte & nummerierte Kleinauflage.

Hergestellt in Wien, Österreich, 2017.

Format:

Platte: 30 x 30cm

Hülle: 31 x 31cm

Material/Technik:

Platten: Siebdruck auf Karton

Hüllen: Siebdruck auf Papier

Steine: Betonguss, tw. gefärbt

Product Design | Time 4 Play

51 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Product Design | Time 4 Play

52 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Product Design | Time 4 Play

53 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Product Design | Rollkoffer roll

Rollkoffer Roll

Produktdesign – Diplomarbeit:

Designobjekt Reisekoffer / Trolley

Universität für angewandte Kunst, Wien, 2007

54 / 55 | ce–design_CarolineEcker_SelectedWorks_1801 Product Design | Rollkoffer roll

DESIGN

CAROLINE ECKER Mag.art+43 660 213 60 26 | [email protected]

http://www.ce-design.org

180131_portfolio-ce_ - ce-design

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